The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
In this paper, we focus on the common problems of current information analysis and support decision systems in agricultural and forestry economies, such as frequent manual interventions, lack of cooperation among sub-systems, lack of support from distributed computing and group decision making. This research aims to resolve these problems by rebuilding the system with agent technology, and a prototype of the agricultural and forestry economy decision_support system (AFEDSS) based on agent is designed and implemented. The AFEDSS is composed of interface agent, management agent, model agent, forecast agent, assistant decision agent, data management agent. The results show that the new system can simulate and deal with the complex processes of agricultural and forestry economies in reasonably short computational times and with less subjective uncertainty. This paper also discusses the decision processes and internal mechanisms in AFEDSS especially on cooperating with dynamic analysis, evaluation, forecast and optimisation.
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